ON THE USE OF GENETIC ALGORITHM TO OPTIMIZE THE ON- BOARD ENERGY MANAGEMENT OF A HYBRID SOLAR VEHICLE

Size: px
Start display at page:

Download "ON THE USE OF GENETIC ALGORITHM TO OPTIMIZE THE ON- BOARD ENERGY MANAGEMENT OF A HYBRID SOLAR VEHICLE"

Transcription

1 Copyright 28, IFP ON THE USE OF GENETIC ALGORITHM TO OPTIMIZE THE ON- BOARD ENERGY MANAGEMENT OF A HYBRID SOLAR VEHICLE Ivan Arsie, Raffaele Di Martino, Gianfranco Rizzo, Marco Sorrentino* Department of Mechanical Engineering, University of Salerno, 8484 Fisciano (SA), Italy, * Corresponding author Abstract ON THE USE OF GENETIC ALGORITHM TO OPTIMIZE THE ON-BOARD ENERGY MANAGEMENT OF A HYBRID SOLAR VEHICLE This paper deals with the development of a prototype of Hybrid Solar Vehicle (HSV) with series structure. This activity has been also conducted in the framework of the EU funded Leonardo project Energy Conversion Systems and Their Environmental Impact, a project with research and educational objectives. A study on supervisory control for hybrid solar vehicles and some preliminary tests performed on the road are presented. Previous results obtained by a model for HSV optimal design have confirmed the relevant benefits of such vehicles with respect to conventional cars in case of intermittent use in urban driving (city-car), and that economical feasibility could be achieved in a near future. Due to the series-powertrain adopted for the HSV prototype, an intermittent use of the ICE powering the electric generator is possible, thus avoiding part-load low-efficient engine operations. The best ICE power trajectory is determined via genetic algorithm optimization accounting for fuel mileage as well as battery state of charge, also considering solar contribution during parking mode. The experimental set up used for data logging, real-time monitoring and control of the prototype is also presented, and the results obtained with different road tests discussed. INTRODUCTION Sustainable Mobility issues are gaining increasing attention both among specialists and in public opinion, due to the major impact of automotive systems on carbon dioxide production, climate changes and fossil fuel depletion. Recently, increasing efforts are being spent towards the application of solar energy to electric and hybrid cars. While solar vehicles do not represent a practical alternative to cars for normal use, the concept of a hybrid electric car assisted by solar panels appears more realistic [1]. In fact, thanks to a relevant research effort, in the last decade Hybrid Electric Vehicles (HEV) have evolved to industrial maturity, and represent now a realistic solution to important issues, such as the reduction of gaseous pollution in urban drive as well as the need for a substantial increase of energy conversion efficiencies. On the other hand, the use of solar energy on cars has been considered with a certain skepticism by most users, including automotive engineers. This may be due to the simple observation that the net power achievable in a car with current photovoltaic panels is about two order of magnitude less than maximum power of most of today cars. But a more careful analysis of the energy involved demonstrate that this perception may be misleading. In fact, there is a large number of drivers utilizing daily their car for short trips and with limited power demand [2]. In those conditions, the solar energy collected by solar panels on the car along a day may represent a significant fraction of the energy required for traction [3]. In spite of their potential interest, solar hybrid cars have received relatively little attention in literature. Some prototypes have been developed or are under current development [4]. Although these works demonstrate the general feasibility of such an idea, detailed presentation of results and performance, along with a systematic approach to solar hybrid vehicle design, seem still missing in literature. Therefore, appropriate methodologies are required to address both the rapid changes in the technological scenario and increasing availability of innovative, more efficient components and solutions. A specific difficulty in developing a Hybrid Solar Vehicle relates to the many mutual interactions between energy flows, powertrain balance of plant and sizing, vehicle dimension, performance, weight and costs, whose connections are much more critical than in either conventional or hybrid electric vehicles. Moreover, the control strategies for HSV cannot be simply derived from the solutions developed for HEV. In fact, the presence of solar panels requires to extend the SOC management strategies also to parking phases, while the study of suitable control techniques is needed in order to maximize the net power

2 from solar panels [5]. Finally, many HSV prototypes tend to adopt a series structure, while most of today HEV adopt a parallel or series/parallel approach. Series structure appears more suitable for plug-in hybrid applications [6], and is compatible with the use of inwheel motors with built-in traction control and anti-skid [7]. Moreover, the series configuration represents a natural bridge towards the introduction of fuel cell hybrid vehicles. mechanical power for the propulsion or restore part of the braking power during regenerative braking. In this structure, the thermal engine can work mostly at constant power, corresponding to its optimal efficiency, while the electric motor EM is designed to assure the attainment of the vehicle peak power. This paper deals with modeling, on-board energy management and performance evaluation for a prototype of Hybrid Solar Vehicle with series structure. This activity has been started in the framework of the UE funded Leonardo project Energy Conversion Systems and Their Environmental Impact [8], a project with research and educational objectives. 1 THE HSV PROTOTYPE Table I lists the main features and specifications of the HSV prototype (see Figure 1), now under-development at DIMEC-UNISA lab facilities. Figure 1: The Hybrid Solar Vehicle Prototype. Table 1: Actual HSV prototype specifications. Vehicle Piaggio Porter Length 3.37 m Width m Height 1.87 m Drive ratio 1:4.875 Electric Motor BRUSA MV 2 84 V Continuous Power 9 KW Peak Power 15 KW Batteries 16 6V Modules Pb- Gel Mass 52 Kg Capacity 18 Ah Photovoltaic Panels Polycrystalline Surface A PV 1.44 m 2 Weight 6 kg Efficiency (including.1 converter) Electric Generator Yanmar S 6 Power COP/LTP 5.67/6.92 kva Weight 12 kg Overall weight (w driver) M HSV 195 kg Vehicle lay-out is organized according to a series hybrid architecture, as shown on Figure 2. With this approach, the photovoltaic panels PV (placed on vehicle roof as shown on Figure 1) assist the Electric Generator EG, powered by an Internal Combustion Engine (ICE), in recharging the Battery pack (B) in both parking mode and driving conditions, through the Electric Node (EN). The Electric Motor (EM) can either provide the Figure 2: Scheme of the series hybrid solar vehicle. 2 HSV MODELING AND EXPERIMENTAL CHARACTERIZATION HSV simulation, whose results are presented in Section 4, was performed by means of a longitudinal vehicle model developed under the following hypotheses: i) drag (C x ) and rolling (C r ) coefficients are assumed equal to.4 and.2, respectively; ii) the drag force is considered acting on vehicle centre of gravity; iii) overall transmission efficiency η tr is set to.9; iv) rotational inertia is accounted for increasing vehicle weight by 1%, therefore effective mass M eff equals 1.1 M HSV. The resulting longitudinal model relates requested power at wheels to the road load, as follows: Pw = M HSV g v dv + Meff v dt [ C cos( α ) + sin( α )] r 3 +.5ρ Cx Av + where α and v are the road grade and vehicle speed, respectively. For non negative P w values, the mechanical power requested to the EM is: (1)

3 PEM P = w if Pw ηtr (2).35.3 Experimental Simulated η EG [/] P EM can also be expressed as function of power contributions coming from electric generator, battery and PV array, as follows: PEM η ( P η + P + P ) if P (3) = EG AC / DC B PV w EM.1.5 where P x is the power supplied by the x component (i.e. electric generator, battery and photovoltaic panels), η EM is the EM efficiency and η AC/DC is the AC/DC converter efficiency, here set to.92. On the other hand, when P w <, the regenerative braking mode is active, resulting in the following expression for the electrical energy delivered by the EM: PEM = Pw η tr ηem if Pw < (4) During regenerative braking, battery can be charged by EG and PV also, thus the following equation holds for negative P w values: PB = PEM PEG η AC / DC PPV if Pw < (5) 2.1 Electric generator The electric generator, is composed of a Diesel engine, one cylinder, 46 cm 3, coupled with a 3 phase synchronous induction machine. Experiments were carried out to map the efficiency of the electric generator in a wide operating region, accounting for the whole path from fuel to electrical power. The experimental set-up was arranged with a 3-phase pure resistive, balanced electrical load. The measurements were accomplished at constant engine speed (3 rpm), corresponding to a 5 Hz electric signal, with regularly spaced variation of electrical load by steps of 6 W, up to 54 W. Figure 3 shows the experimental EG efficiency vs. the output power of the electrical generator (EG). The efficiency was detected by processing the measurements of fuel consumption and output voltage and current, as follows: PEG V I EG = = m& f H i m& f H i η (6) Power [KVA] Figure 3: Comparison between experimental and predicted electric generator efficiency. 2.2 PV array Regarding the PV energy contribution to vehicle traction, it was computed on the basis of real energy measurements collected on a stationary PV plant located within UNISA area. The measured energy distribution results in the following daily average evaluated on a year basis: Esun day = 3. 1 kwh kwp day, (7) Considering the PV roof efficiency of 1%, a nominal power of 1kW can be obtained with a 1/.1=1 m 2 array. Therefore, daily average energy yielded by the 1.44 m 2 PV roof (see Table 1) can be estimated as follows: APV 1.44 EPV = Esun, day = 3.1 = 45 [ Wh / day] (8) Battery pack The battery pack model estimates battery state of charge (SOC), current and thermal state as function of the actual electrical power (i.e. positive in discharge and negative in charge). The actual current is computed starting from the electrical power, by applying the Kirchoff s law to the equivalent circuit shown on Figure 4. The internal resistance R in was modeled, following the approach proposed by [9], as a nonlinear function of battery temperature and state of charge. Figure 5 focuses on the effect of SOC, showing high charge and discharge resistance at high and low SOC, respectively. In Figure 3 the efficiency predicted by a black box model identified vs. the experimental data is also plotted. The model expresses the overall efficiency of the electric generator as function of the output electrical power by a 4th order polynomial regression.

4 E R in V r I dis E = battery open circuit voltage V r = internal voltage losses I dis = discharging current R in a) V batt E b) V r I chg V batt R in = battery internal resistance V batt = effective voltage I chg = charging current Figure 4: Equivalent circuit of the battery pack [a) discharge; b) charge]. The battery model accuracy was checked by comparing simulated data with experiments conducted both in case of battery discharging and charging (see Figure 6). The agreement between experiments and model outputs confirms the validity of extending the model proposed by [9] to the battery pack the HSV prototype is equipped with. It is worth mentioning that the data shown in Figure 6 refer to initial SOC values of 1 and.6 for battery discharging and charging, respectively Battery internal resistance [Ohm] Discharge Charge State of charge [/] Figure 5: Variation of battery internal resistance in charging and discharging as function of SOC [9] Battery voltage [V] in discharge operation mode (a) Experimental Battery Model Battery voltage [V] in charge operation mode (b) 6.6 Experimental 6.4 Battery Model Current [A] Figure 6: Comparison between model [9] and experimental data collected during battery discharging and charging. 2.4 Electric motor The efficiency of the electric motor (EM) is simulated by a black box model identified vs. the technical data sheets provided by motor manufacturer. The model expresses the efficiency as function of the mechanical power provided for the propulsion via a 3 rd order polynomial regression. Figure 7 shows both experimental and simulated efficiency vs. provided power η EM [/].7 experimental simulated Power [KW] Figure 7: Comparison between experimental and predicted electric motor efficiency vs. provided power. 3 OPTIMAL ENERGY MANAGEMENT ON HSV VEHICLES Hybrid Solar Vehicles have of course many similarities with Hybrid Electric Vehicles, for which many studies on the optimal management and control of energy flows have been presented in last years [1 14]. Nevertheless, the presence of solar panels and the adoption of a series structure may require to study and develop specific solutions for optimal management and control of an HSV. In fact, in most electric hybrid vehicles a charge sustaining strategy is adopted: at the end of a driving path, the battery state of charge should remain unchanged. With a solar hybrid vehicle, a different strategy should be adopted as battery is charged during parking hours as well. In this case, a different goal can be pursued, namely restoring the initial state of charge within the end of the day rather than after a single driving path [15]. Moreover, the series configuration suggests quite an efficient solution, namely to operate the engine in an intermittent way at constant operating conditions. Of course, the maximum gain in terms of fuel consumption occurs when the EG power corresponds to the most efficient value. In such case, the engine-generator system may be designed and optimized to maximize its efficiency, emissions and noise at design point, while in current automotive engines the maximum efficiency is usually sacrificed to the need of assuring stable

5 operation and good performance in the whole operating range. In order to develop a supervisory control to be implemented on the vehicle, a more accurate analysis of the optimal EG power distribution over an arbitrary driving cycle has to be performed. This task is discussed in the next sub-section. 3.1 Optimization of electric generator scheduling by means of genetic algorithms The optimal EG power trajectory can be found by solving the following constrained optimization problem. ( X ) min X m& f, HSV dt (9) subject to the constraints: SOC day = SOC f SOC + SOCp = (1) SOC > SOC min (11) SOC < SOC max (12) where m & f, HSV is the HSV fuel consumption [kg], SOC f and SOC are the initial and final state of charge in the driving phase, respectively, and SOC p is the SOC increase due to PV recharging during vehicle parking. The decision variables X include number of EG-on events N EG, along with corresponding starting time t,eg,i, duration t,eg,i and EG power level P EG,i, where i is the i- th EG-on event. The first constraint (Eq. 1) allows to restore the initial state of charge within the end of the day, also considering parking phases. It is worth noting that the proposed energy management strategy is based on the knowledge of the vehicle route. Future activities will focus on the extension of the optimization outcomes to different driving scenarios as well as insolation conditions. The other constraints (i.e. Eqs. 11and 12) were defined accounting for internal resistance dependence on battery state of charge. Figure 5 shows that in the SOC range [.55.9] both charging and discharging resistances are fairly constant while being close to their minimum values. Therefore in this analysis SOC min and SOC max were set to.55 and.9, respectively. The problem stated by Eqs. (9) through (12) involves both integer (e.g. N EG ) and real variables, thus falling in the field of Mixed Integer Programming (MIP) problems. Among the several techniques that can be adopted to solve such problems, genetic algorithms (GA) is one of the most efficient [16] and has thus been selected for optimizing EG scheduling on the HSV prototype. The GA search was performed in Matlab environment by means of the GAtbx tool developed by [17]. GA optimization consists of an iterative procedure that can be schematized as follows: Phase 1: an initial population of N ind individuals (or solutions) representing the search domain (i.e. the decision variables domain) is generated randomly. Phase 2: An objective function F is evaluated for each individual. Then, assuming that a minimization task is being accomplished, all the individuals are ranked in ascending order on the basis of their F k value. This way the so-called fitness is assigned to the k-th individual, whose value will range from a maximum to a minimum depending on its rank position. Phase 3: Fitness-based selection of best individuals. According to the evolutionary theory, the best individuals have the highest probability to join the next population. The Roulette Wheel and Stochastic Universal Sampling [17] are among the most widely adopted techniques to perform a random selection of the strongest individuals as function of their fitness. Particularly, the higher its fitness is, the more likely that individual will be selected. In this work, the latter method was applied. Phase 4: Generation of new individuals. Phase 3 usually yields a new set of individuals containing a higher number of strong (i.e. with high fitness) solutions, whereas some of the weakest ones disappear. This intermediate set undergoes a renewal process consisting of two different steps: crossover and mutation. The former step basically makes a certain number of individual pairs, selected randomly, to exchange part of their genotype with each other. The resulting genotypes will of course behave differently in the next population, thus yielding a couple of new individuals. After crossover, mutation takes place, once again based on random selection of some individuals. It is worth mentioning that an elitist approach is usually followed in Phase 4, in that some of the strongest individuals from the current population are ensured to be present in the next one. This way, even though a lower number of off-springs is introduced, the best solutions from the current population are preserved [17]. Phase 2 through Phase 4 are repeated as many times as the desired number of new generations is reached. The above description highlights the need for the decision maker to select several operating parameters (Nind, crossover and mutation probabilities, number of

6 generations) depending on problem complexity and computational time requirements. Further details about GA optimization techniques can be found in the abundant literature on the topic, which the reader is addressed to [16 19]. For the current application, the following operating parameters were assumed: Table 2 GA operating parameters. N ind 5 Number of generations 3 Crossover probability.7 Mutation probability.6 Regarding the binary representation to define the individual genotype, the number of bits per each decision variable was calculated according to the information provided in Table 3: Table 3 Binary representation of the optimization problem. Decision Definition Number of Precision variable range bits N EG [1 4] 1 2 t EG (min) [ 53].55 1 t EG (min) [ 53].55 1 P EG (kw) [ 5.5] SCENARIO ANALYSIS In order to assess the HSV prototype performance not only at the current developmental stage, but also analyzing two further scenarios of improved vehicle configurations, a simulation analysis was performed. Such an analysis was accomplished by solving, in a backward manner, the longitudinal vehicle dynamics (i.e. Eq. 1) for a driving cycle composed of 4 ECE cycles, as the one shown on Figure Results Table 4 summarizes the results obtained in the three analyzed scenarios. Particularly, it emerges that an acceptable fuel economy can be obtained even with current vehicle configuration (i.e. scenario 1). This is possible thanks to the high efficient use of the Diesel engine addressed by the GA based optimization described above. Particularly, Figure 9 shows that the Diesel engine is turned on once, after 15 minutes, delivering 5 kw to battery and/or EM for about 25 minutes. This allowed to operate the EG itself at an overall efficiency as high as.28 (see Figure 3). The EG energy contribution caused battery to partially recover the state of charge reduction occurred in the first part of the driving cycle, resulting in a final SOC of.732, as shown on Figure 1. The lower value of SOC with respect to the initial one is in accordance with the constraint expressed by Eq. (1) Vehicle speed [km/h] Time [min] Figure 8: Module of ECE driving cycle. Regarding the other scenarios, it is worth mentioning here that the second scenario corresponds to an optimized vehicle configuration, in which a.18 efficient PV array (i.e. E PV = 81 Wh/day) replaces the actual one and battery capacity is lowered down to 75 Ah. The latter hypothesis takes into account the impact of vehicle hybridization, as the added electric generator allows to reduce both battery storable energy and nominal power. The lower battery capacity also causes the weight to decrease from 195 kg to 1658 kg. Such a configuration results in a fuel economy improvement up to 22 km/liter, as indicated in Table 4. Figure 11 shows that in scenario 2 the optimal EG scheduling addressed by the GA optimization consists of two EG-on events and lower average EG power with respect to scenario 1, which in turn results in a lower energy contribution by the EG. This is linked to the lower final SOC to be reached at the end of the driving phase (see Figure 1) as compared to scenario 1. The low final SOC (about.675) is due to the higher amount of solar energy and the lower battery capacity simulated in scenario 2. In conclusion, both weight reduction and PV efficiency increase contribute to achieve the fuel economy improvement. Particularly, the fuel saving is equivalent to.2 liter in the reference transient and is due by 56% to weight reduction and by 44% to PV efficiency. Finally, the third scenario was considered to account for a further weight reduction (i.e. 2%), obtainable by improving vehicle materials [3]. The simulated fuel economy in this case gets close to 3 km/liter. As in scenario 2, the final SOC sets to.675, as shown on Figure 1. On the other hand, the energy contribution requested to the EG is further low as compared to scenario 2, due to the lower vehicle weight assumed in scenario 3. In order to maximize fuel economy, this time the GA optimization yielded a solution with 3 EG-on events, each one with shorted duration than scenario 2 but similar average power, as shown on Figure 11.

7 Table 4 HSV simulation results. Scenario η PV EG Power [kw] Scenario 2 Scenario 3 Battery capacity (Ah) M hsv Fuel economy (km/liter) Power [kw] - dotted line=battery; continuous=eg Time [min] 5 Figure 11: EG power trajectories for scenarios 2 and Time [min] Figure 9: EG and battery power trajectories for scenario Battery state of charge (SOC) [/] 5 MEASUREMENT SYSTEM ON THE VEHICLE The prototype has been equipped with a measurement system for real-time monitoring and data logging. Two experiments have been also carried out using different road tests. Schematically, the measure chain is reported in Fig.12. Moreover, the measurement system Ni C-Rio provides the acquisition vehicle torque while the solar prototype is running. A scheme of these measurements is shown in Fig E.M. Electric Machine Current Electric Machine Voltage Electric Machine Velocity Electric Machine Torque.75 Sensor Signals D. Brake Pedal Position Throttle Pedal Position Vehicle Dynamic s.7 Scenario 1 Scenario 2 Scenario Time [min] Vehicle E.G. B. Electric Generator Velocity Electric Generator Current Electric Generator Voltage Battery Pack Current Battery Pack Voltage Data Logging Figure 1: SOC trajectories for all simulated scenarios. Disturbances S. Solar Irradiation Fig. 12 Schematic representation of the acquisition system. DC Converter Mascot Electronics 8862 HBM AE 11 Signal Amplifier Torsiometer NI C-Rio Controller Fig. 13 Measurement Scheme carried out for the torque real-time monitoring.

8 5.1 Experimental results on the vehicle 12 Torque [Nm] and Longitudinal Velocity [Km/h] torque Some preliminary on-road tests were performed to measure the electric current in different vehicle conditions vehicle speed Fig. 14 shows the brake and traction maneuvers imposed during the first test. As expected, when the driver brakes (e.g. at approximately 25 seconds in Fig. 14 (a)) the electric machine switches to generator operation, thus charging the battery pack with current down to -5 Amps (see Fig. 14 (b)). Then, when the driver presses the accelerator pedal, the current sudden increases above 3 Amps for few seconds, before decaying towards steady-state operation (i.e. around 1 Amps), as shown on Fig. 14 (b). The on-going activity is directed to the completion of the vehicle measurement system, in order to perform a detailed validation of vehicle dynamic models. Other data have been collected during accelerationdeceleration maneuvers (Fig. 15) and for slope-up and slope-down maneuvers (Fig.16) acceleration and brake pedal position [%] - (a) accelerator brake Time [s] Battery current [A] - (b) Time [s] Fig. 14 Experimental results collected in the first road test Net Torque [Nm] and Longitudinal Velocity [km/h] Vehicle Velocity Net Torque Time [s] Slope-up Fig. 16 Experimental results collected in the third road test. 6 CONCLUSIONS The paper reported on the actual developmental stage of a hybrid solar vehicle prototype. The experimental and numerical activities conducted to develop and validate a comprehensive HSV model were presented. The model accounts for vehicle longitudinal dynamics along with the accurate evaluation of energy conversion efficiency for each powertrain component. Genetic algorithm optimization was proposed to address some of the most challenging issues in the development of hybrid solar vehicles with series structure, namely the definition of the optimal electric generator scheduling. Actual vehicle performance and fuel economy were analyzed by simulating the HSV prototype on a driving route composed of 4 ECE cycles. The resulting fuel consumption was 15 km/liter. Further simulations showed that fuel economy can be increased up to 3 km/liter both by substituting the actual PV array with more advanced solar technology and by appropriately resizing HSV components. On-going and future activities focus on numerical, experimental and prototype developmental tasks. Particularly, the procedure proposed to define the optimal EG scheduling via genetic algorithm optimization will be extended to optimal energy management of HSV in presence of varying insolation and lack of a-priori knowledge of driving route. In parallel, suited on theroad test and measurements will be performed to validate both simulation results and control strategies effectiveness. Regarding prototype improvements, the installation of an automated sun-tracking roof to further enhance solar energy captation is under current study. ACKNOWLEDGMENTS Slope-down Time [s] Fig. 15 Experimental results collected in the second road test. The authors would like to acknowledge the European Union, the Italian Ministry of University and Research and the University of Salerno for their support to the research activity presented in this paper. REFERENCES

9 1. Neil C., 26, Solar Hybrid Vehicles, Energy Pulse, available at 2. Statistics for Road Transport, available at ID= Arsie I., Marotta M., Pianese C., Rizzo G., Sorrentino M., 25, Optimal Design of a Hybrid Electric Car with Solar Cells, Proc. of 1st AUTOCOM Workshop on Preventive and Active Safety Systems for Road Vehicles, Istanbul, Sept Fiat Phylla, 28, cars/fiat/fiat-phylla-concept-previews-new-topolinoelectric-minicar/. 5. Petrone, G., Femia, N., Spagnuolo, G., Vitelli M., 25, Optimization of perturb and observe maximum power point tracking method, IEEE Transactions on Power Electronics. Vol. 2, pp Letendre S., Perez R., Herig C., 23, Vehicle Integrated PV: A Clean and Secure Fuel for Hybrid Electric Vehicles, Proc. of the American Solar Energy Society Conference, June 21-23, Austin,TX Leonardo Program Energy Conversion Systems and Their Environmental Impact, 9. Burch, S., Cuddy, M., Johnson, V., Markel, T., Rausen, D., Sprik, S., Wipke, K., "ADVISOR: Advanced Vehicle Simulator", available at 1. Powell, B.K., Bailey, K.E., Cikanek, S.R., 1998, Dynamic modeling and Control of Hybrid Vehicle Powertrain Systems, IEEE Trans.Contrl Syst., vol. 18, no. 5, Baumann, B., Rizzoni, G., Washington, G., 1998, Intelligent Control of Hybrid Vehicles using Neural Networks and Fuzzy Logic, SAE paper Guzzella L., Amstutz, A., 1999, CAE Tools for Quasi-Static Modeling and Optimization of Hybrid Poweretrains, IEEE Transactions on Vehicular Technology, vol. 48, no. 6, November Arsie, I., Graziosi, M., Pianese, C., Rizzo, G., Sorrentino, M., 25, Optimization of Supervisory Control Strategy for Parallel Hybrid Vehicle with Provisional Load Estimate, JSAE Review of Automotive Engineering, Vol. 26, No. 3, pp , Arsie, I., Di Martino, R., Rizzo, G., Sorrentino, M., 28, Energy Management for a Hybrid Solar Vehicle with Series Structure, Proc. of the 17th IFAC World Congress, July 6-11, 28, Seoul, Korea. 15. Arsie, I., Rizzo, G., Sorrentino, M., 27, Optimal Design and Dynamic Simulation of a Hybrid Solar Vehicle, SAE paper , SAE Transactions Journal of Engines, vol Sakawa, M., Kato, K., Ushiro, S., Inaoka, M., 21, Operation planning of district heating and cooling plants using genetic algorithms for mixed integer programming, Applied Soft Computing Vol.1, pp Chipperfield, A.J., Fleming, P.J., Polheim, H., Fonseca, C.M., Genetic Algorithm Toolbox Matlab Tutorial, Department of Automatic Control and System Engineering - University of Sheffield, downloadable at l. 18. Chipperfield, A.J., Fleming, P.J., Fonseca, C.M., 1994, Genetic Algorithm Tools for Control Systems Engineering, Proc. Adaptive Computing in Engineering Design and Control, Plymouth Engineering Design Centre, September, pp , Zitzler, E., 1999, Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications, Ph.D. Thesis, ETH Swiss Federal Institute of Technology, Zurich, Switzerland.

On the Use of Genetic Algorithm to Optimize the On-board Energy Management of a Hybrid Solar Vehicle

On the Use of Genetic Algorithm to Optimize the On-board Energy Management of a Hybrid Solar Vehicle Oil & Gas Science and Technology Rev. IFP, Vol. 65 (21), No. 1, pp. 133-143 Copyright 29, Institut français du pétrole DOI: 1.2516/ogst/2935 IFP International Conference Rencontres Scientifiques de l IFP

More information

Model Based Control of a Moving Solar Roof for a Solar Vehicle

Model Based Control of a Moving Solar Roof for a Solar Vehicle Model Based Control of a Moving Solar Roof for a Solar Vehicle G.Coraggio*, C.Pisanti*, G.Rizzo*, A.Senatore* *Dept. Of Mechanical Engineering, University of Salerno, 8484 Fisciano (SA), Italy Email: gcoraggio

More information

An Analysis of Regenerative Braking and Energy Saving for Electric Vehicle with In-Wheel Motors

An Analysis of Regenerative Braking and Energy Saving for Electric Vehicle with In-Wheel Motors , pp. 219-23 http://dx.doi.org/1.14257/ijca.214.7.12.2 An Analysis of Regenerative Braking and Energy Saving for Electric Vehicle with In-Wheel Motors 1 Li-qiang Jin, 2 Peng-fei Chen and 3 *Yue Liu State

More information

ELECTRIFICATION OF VEHICLE DRIVE TRAIN THE DIVERSITY OF ENGINEERING CHALLENGES

ELECTRIFICATION OF VEHICLE DRIVE TRAIN THE DIVERSITY OF ENGINEERING CHALLENGES ELECTRIFICATION OF VEHICLE DRIVE TRAIN THE DIVERSITY OF ENGINEERING CHALLENGES A3PS Conference, Vienna Dr. Frank Beste AVL List GmbH 1 Motivation for Powertrain Electrification Global Megatrends: Urbanization

More information

Sustainable mobility: the Italian technological challenge

Sustainable mobility: the Italian technological challenge Sustainable mobility: the Italian technological challenge an innovative paradigm for a new vehicles' generation ANFIA-ANIE ANIE WORKSHOP Hannover Messe 2010, April 19th Ing. Pier Luigi Farina DUCATI energia:

More information

Model-based Parameter Optimization of an Engine Control Unit using Genetic Algorithms

Model-based Parameter Optimization of an Engine Control Unit using Genetic Algorithms Symposium on Automotive/Avionics Avionics Systems Engineering (SAASE) 2009, UC San Diego Model-based Parameter Optimization of an Engine Control Unit using Genetic Algorithms Dipl.-Inform. Malte Lochau

More information

Fuel Economy Sensitivity to Vehicle Mass for Advanced Vehicle Powertrains

Fuel Economy Sensitivity to Vehicle Mass for Advanced Vehicle Powertrains 26-1-665 Sensitivity to Vehicle Mass for Advanced Vehicle Powertrains Copyright 26 Society of Automotive Engineers, Inc S. Pagerit, P. Sharer, A. Rousseau Argonne National Laboratory ABSTRACT In 22, the

More information

Hybrid reformulation based on a new hybrid Ohm s law for an electrical energy hybrid systems

Hybrid reformulation based on a new hybrid Ohm s law for an electrical energy hybrid systems Hybrid reformulation based on a new hybrid Ohm s law for an electrical energy hybrid systems SANG C. LEE* Division of IoT-Robot convergence research DGIST 333, Techno jungang, Dalseong-Gun, Daegu Republic

More information

Elektrofahrzeug mit Range Extender die Entwicklungsherausforderung Electric Vehicle with Range Extender. The developement challenge

Elektrofahrzeug mit Range Extender die Entwicklungsherausforderung Electric Vehicle with Range Extender. The developement challenge Elektrofahrzeug mit Range Extender die Entwicklungsherausforderung Electric Vehicle with Range Extender Dr. M. Korman AVL-List GmbH The developement challenge Stärkung regionaler Kooperationen in der Elektromobilität

More information

Energy efficiency and fuel consumption of fuel cells powered test railway vehicle

Energy efficiency and fuel consumption of fuel cells powered test railway vehicle Energy efficiency and fuel consumption of fuel cells powered test railway vehicle K.Ogawa, T.Yamamoto, T.Yoneyama Railway Technical Research Institute, TOKYO, JAPAN 1. Abstract For the purpose of an environmental

More information

Physical Modeling with SimScape

Physical Modeling with SimScape Physical Modeling with SimScape Saving energy with Physical Modeling Adriaan van den Brand Mday 29-4-2011 V1.4 A. Van den Brand, Mday 29-4-2011 1 Bio Adriaan van den Brand System architect Sogeti High

More information

Modelling and optimization of renewable energy supply for electrified vehicle fleet

Modelling and optimization of renewable energy supply for electrified vehicle fleet Modelling and optimization of renewable energy supply for electrified vehicle fleet Dipl. Ing. Torsten Schwan Dipl. Ing. René Unger EA Systems Dresden GmbH Prof. Dr. Ing. Bernard Bäker Institute of Automotive

More information

Performance Study based on Matlab Modeling for Hybrid Electric Vehicles

Performance Study based on Matlab Modeling for Hybrid Electric Vehicles International Journal of Computer Applications (975 8887) Volume 99 No.12, August 214 Performance Study based on Matlab Modeling for Hybrid Electric Vehicles Mihai-Ovidiu Nicolaica PhD Student, Faculty

More information

Analysis of fuel cell

Analysis of fuel cell Analysis of fuel cell commuter rail vehicles Stuart Hillmansen*1 1, D Meegahawatte1, C Roberts, P Jennings2, A McGordon2; 1University of Birmingham, United Kingdom, 2University of Warwick, United Kingdom

More information

48V eco-hybrid Systems

48V eco-hybrid Systems 48V eco-hybrid Systems Jean-Luc MATE Vice President Continental Engineering Services France President Automotech cluster www.continental-corporation.com Division Naming European Conference on Nanoelectronics

More information

K.Vijaya Bhaskar,Asst. Professor Dept. of Electrical & Electronics Engineering

K.Vijaya Bhaskar,Asst. Professor Dept. of Electrical & Electronics Engineering Incremental Conductance Based Maximum Power Point Tracking (MPPT) for Photovoltaic System M.Lokanadham,PG Student Dept. of Electrical & Electronics Engineering Sri Venkatesa Perumal College of Engg & Tech

More information

Development of a software tool to evaluate the energetic and environmental impact of Electric and Hybrid Vehicles in Brussels

Development of a software tool to evaluate the energetic and environmental impact of Electric and Hybrid Vehicles in Brussels Development of a software tool to evaluate the energetic and environmental impact of Electric and Hybrid Vehicles in Brussels Ir. J. Van Mierlo Ir. W. Deloof Prof. Dr. Ir. G. Maggetto Vrije Universiteit

More information

Field experience and best practices in managing MW scale Li-ion energy storage systems coupled to large wind and solar plants

Field experience and best practices in managing MW scale Li-ion energy storage systems coupled to large wind and solar plants Field experience and best practices in managing MW scale Li-ion energy storage systems coupled to large wind and solar plants Michael Lippert & Jesus Lugaro IRES Düsseldorf 1 March 215 Summary 1. Characterization

More information

Doctoral School on Engineering Sciences Università Politecnica delle Marche

Doctoral School on Engineering Sciences Università Politecnica delle Marche Doctoral School on Engineering Sciences Università Politecnica delle Marche Extended summary Knowledge-based approaches to support the design and development of the electrochemical storage Scuola di Dottorato

More information

Comparison Control Strategies for ISG hybrid electric vehicle. Hailu Tang 1, a

Comparison Control Strategies for ISG hybrid electric vehicle. Hailu Tang 1, a 3rd International Conference on Mechatronics, Robotics and Automation (ICMRA 2015) Comparison Control Strategies for ISG hybrid electric vehicle Hailu Tang 1, a School of Automotive Engineering,Wuhan University

More information

A Moving Solar Roof for a Hybrid Solar Vehicle

A Moving Solar Roof for a Hybrid Solar Vehicle A Moving Solar Roof for a Hybrid Solar Vehicle G.Coraggio*, C.Pisanti*, G.Rizzo*, A.Senatore* *Dept. of Mechanical Engineering, University of Salerno, 884 Fisciano (SA), Italy Email: gcoraggio - cpisanti

More information

Transient analysis of integrated solar/diesel hybrid power system using MATLAB Simulink

Transient analysis of integrated solar/diesel hybrid power system using MATLAB Simulink Transient analysis of integrated solar/diesel hybrid power system using ATLAB Simulink Takyin Taky Chan School of Electrical Engineering Victoria University PO Box 14428 C, elbourne 81, Australia. Taky.Chan@vu.edu.au

More information

Short-term Forecast for Photovoltaic Power Generation with Correlation of Solar Power Irradiance of Multi Points

Short-term Forecast for Photovoltaic Power Generation with Correlation of Solar Power Irradiance of Multi Points Short-term Forecast for Photovoltaic Power Generation with Correlation of Solar Power Irradiance of Multi Points HIROAKI KOBAYASHI Polytechnic University / Kogakuin University 2-32-1 Ogawanishi-machi,

More information

Power Quality For The Digital Age INVERTING SOLAR POWER A N E N V IRONME N TA L P OT E N T I A L S W HI T E PA PER. www.ep2000.com 800.500.

Power Quality For The Digital Age INVERTING SOLAR POWER A N E N V IRONME N TA L P OT E N T I A L S W HI T E PA PER. www.ep2000.com 800.500. Power Quality For The Digital Age INVERTING SOLAR POWER A N E N V IRONME N TA L P OT E N T I A L S W HI T E PA PER Introduction Heat in the System The modern facility has been revolutionized by advancements

More information

Gasoline engines. Diesel engines. Hybrid fuel cell vehicles. Model Predictive Control in automotive systems R. Scattolini, A.

Gasoline engines. Diesel engines. Hybrid fuel cell vehicles. Model Predictive Control in automotive systems R. Scattolini, A. Model Predictive Control in automotive systems R. Scattolini, A. Miotti Dipartimento di Elettronica e Informazione Outline Gasoline engines Diesel engines Hybrid fuel cell vehicles Gasoline engines 3 System

More information

SOFTWARE FOR THE OPTIMAL ALLOCATION OF EV CHARGERS INTO THE POWER DISTRIBUTION GRID

SOFTWARE FOR THE OPTIMAL ALLOCATION OF EV CHARGERS INTO THE POWER DISTRIBUTION GRID SOFTWARE FOR THE OPTIMAL ALLOCATION OF EV CHARGERS INTO THE POWER DISTRIBUTION GRID Amparo MOCHOLÍ MUNERA, Carlos BLASCO LLOPIS, Irene AGUADO CORTEZÓN, Vicente FUSTER ROIG Instituto Tecnológico de la Energía

More information

EMI in Electric Vehicles

EMI in Electric Vehicles EMI in Electric Vehicles S. Guttowski, S. Weber, E. Hoene, W. John, H. Reichl Fraunhofer Institute for Reliability and Microintegration Gustav-Meyer-Allee 25, 13355 Berlin, Germany Phone: ++49(0)3046403144,

More information

Robotics & Automation

Robotics & Automation Robotics & Automation Levels: Grades 10-12 Units of Credit: 1.0 CIP Code: 21.0117 Core Code: 38-01-00-00-130 Prerequisite: None Skill Test: 612 COURSE DESCRIPTION Robotics & Automation is a lab-based,

More information

2006 Honda Civic-8725 Hybrid Battery Test Results

2006 Honda Civic-8725 Hybrid Battery Test Results 2006 Honda Civic-8725 Hybrid Battery Test Results HEVAMERICA U.S. DEPARTMENT OF ENERGY ADVANCED VEHICLE TESTING ACTIVITY Hybrid System Specifications Battery Specifications Manufacturer: Panasonic Battery

More information

The Quest for Energy Efficiency. A White Paper from the experts in Business-Critical Continuity

The Quest for Energy Efficiency. A White Paper from the experts in Business-Critical Continuity The Quest for Energy Efficiency A White Paper from the experts in Business-Critical Continuity Abstract One of the most widely discussed issues throughout the world today is the rapidly increasing price

More information

dspace DSP DS-1104 based State Observer Design for Position Control of DC Servo Motor

dspace DSP DS-1104 based State Observer Design for Position Control of DC Servo Motor dspace DSP DS-1104 based State Observer Design for Position Control of DC Servo Motor Jaswandi Sawant, Divyesh Ginoya Department of Instrumentation and control, College of Engineering, Pune. ABSTRACT This

More information

KINETIC ENERGY RECOVERY SYSTEM BY MEANS OF FLYWHEEL ENERGY STORAGE

KINETIC ENERGY RECOVERY SYSTEM BY MEANS OF FLYWHEEL ENERGY STORAGE ADVANCED ENGINEERING 3(2009)1, ISSN 1846-5900 KINETIC ENERGY RECOVERY SYSTEM BY MEANS OF FLYWHEEL ENERGY STORAGE Cibulka, J. Abstract: This paper deals with the design of Kinetic Energy Recovery Systems

More information

Introduction to Electronic Signals

Introduction to Electronic Signals Introduction to Electronic Signals Oscilloscope An oscilloscope displays voltage changes over time. Use an oscilloscope to view analog and digital signals when required during circuit diagnosis. Fig. 6-01

More information

On the Influence of Stator Slot shape on the Energy Conservation Associated with the Submersible Induction Motors

On the Influence of Stator Slot shape on the Energy Conservation Associated with the Submersible Induction Motors American Journal of Applied Sciences 8 (4): 393-399, 2011 ISSN 1546-9239 2010 Science Publications On the Influence of Stator Slot shape on the Energy Conservation Associated with the Submersible Induction

More information

Research Report. Impact of Vehicle Weight Reduction on Fuel Economy for Various Vehicle Architectures

Research Report. Impact of Vehicle Weight Reduction on Fuel Economy for Various Vehicle Architectures Impact of Vehicle Weight Reduction on Fuel Economy for Various Vehicle Architectures Research Report Conducted by Ricardo Inc. for The Aluminum Association 2008-04 Impact of Vehicle Weight Reduction on

More information

High Power Programmable DC Power Supplies PVS Series

High Power Programmable DC Power Supplies PVS Series Data Sheet High Power Programmable DC Power Supplies The PVS10005, PVS60085, and PVS60085MR programmable DC power supplies offer clean output power up to 5.1 kw, excellent regulation, and fast transient

More information

System Modelling and Online Optimal Management of MicroGrid with Battery Storage

System Modelling and Online Optimal Management of MicroGrid with Battery Storage 1 System Modelling and Online Optimal Management of MicroGrid with Battery Storage Faisal A. Mohamed, Heikki N. Koivo Control Engineering Lab, Helsinki University of Technology, P.O. Box 5500, FIN-0015

More information

Mixing Sodium and Lead Battery Technologies in Telecom Applications

Mixing Sodium and Lead Battery Technologies in Telecom Applications Mixing Sodium and Lead Battery Technologies in Telecom Applications Paul Smith Shanon Kolasienski Technical Marketing Manager Application Engineer GE Critical Power GE Energy Storage Plano, TX 75074 Schenectady,

More information

hybrid fuel cell bus

hybrid fuel cell bus hybrid fuel cell bus PURE EMOTION PURE capacity The full passenger capacity of a standard diesel bus seats 34 standees 70 (7 passengers per sqm) total 104 Thanks to the three axles of the Van Hool A330

More information

INDUCTION MOTOR PERFORMANCE TESTING WITH AN INVERTER POWER SUPPLY, PART 2

INDUCTION MOTOR PERFORMANCE TESTING WITH AN INVERTER POWER SUPPLY, PART 2 INDUCTION MOTOR PERFORMANCE TESTING WITH AN INVERTER POWER SUPPLY, PART 2 By: R.C. Zowarka T.J. Hotz J.R. Uglum H.E. Jordan 13th Electromagnetic Launch Technology Symposium, Potsdam (Berlin), Germany,

More information

DESIGN AND SIMULATION OF LITHIUM- ION BATTERY THERMAL MANAGEMENT SYSTEM FOR MILD HYBRID VEHICLE APPLICATION

DESIGN AND SIMULATION OF LITHIUM- ION BATTERY THERMAL MANAGEMENT SYSTEM FOR MILD HYBRID VEHICLE APPLICATION DESIGN AND SIMULATION OF LITHIUM- ION BATTERY THERMAL MANAGEMENT SYSTEM FOR MILD HYBRID VEHICLE APPLICATION Ahmed Imtiaz Uddin, Jerry Ku, Wayne State University Outline Introduction Model development Modeling

More information

HRB Hydrostatic Regenerative Braking System: The Hydraulic Hybrid Drive from Bosch Rexroth

HRB Hydrostatic Regenerative Braking System: The Hydraulic Hybrid Drive from Bosch Rexroth HRB Hydrostatic Regenerative Braking System: The Hydraulic Hybrid Drive from Bosch Rexroth Contact Eric Lindzus, Bosch Rexroth AG Bosch Rexroth AG Product Management Sales Mobile Hydraulics Innovative

More information

Harmonics and Noise in Photovoltaic (PV) Inverter and the Mitigation Strategies

Harmonics and Noise in Photovoltaic (PV) Inverter and the Mitigation Strategies Soonwook Hong, Ph. D. Michael Zuercher Martinson Harmonics and Noise in Photovoltaic (PV) Inverter and the Mitigation Strategies 1. Introduction PV inverters use semiconductor devices to transform the

More information

Power Electronics. Prof. K. Gopakumar. Centre for Electronics Design and Technology. Indian Institute of Science, Bangalore.

Power Electronics. Prof. K. Gopakumar. Centre for Electronics Design and Technology. Indian Institute of Science, Bangalore. Power Electronics Prof. K. Gopakumar Centre for Electronics Design and Technology Indian Institute of Science, Bangalore Lecture - 1 Electric Drive Today, we will start with the topic on industrial drive

More information

A Stable DC Power Supply for Photovoltaic Systems

A Stable DC Power Supply for Photovoltaic Systems Int. J. of Thermal & Environmental Engineering Volume 12, No. 1 (216) 67-71 A Stable DC Power Supply for Photovoltaic Systems Hussain A. Attia*, Beza Negash Getu, and Nasser A. Hamad Department of Electrical,

More information

Hybrid Electric Vehicle Architectures

Hybrid Electric Vehicle Architectures Hybrid Electric Vehicle Architectures Series, parallel, mild, strong, full, power-assist, one-mode, twomode.. Tom Bradley and Ken Stanton Objectives Recall the means by which HEVs improve fuel economy

More information

Development of Grid-stabilization Power-storage Systems Using Lithium-ion Rechargeable Batteries

Development of Grid-stabilization Power-storage Systems Using Lithium-ion Rechargeable Batteries 48 Development of Grid-stabilization Power-storage Systems Using Lithium-ion Rechargeable Batteries TSUTOMU HASHIMOTO *1 AKIO KURITA *2 MASAAKI MINAMI *3 MASAHIRO YOSHIOKA *2 KATSUAKI KOBAYASHI *4 MASAYUKI

More information

A Comprehensive Thermal Management System Model for Hybrid Electric Vehicles

A Comprehensive Thermal Management System Model for Hybrid Electric Vehicles A Comprehensive Thermal Management System Model for Hybrid Electric Vehicles by Sungjin Park A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Mechanical

More information

Wind-Diesel Hybrid System Options for Alaska. Steve Drouilhet National Renewable Energy Laboratory Golden, CO

Wind-Diesel Hybrid System Options for Alaska. Steve Drouilhet National Renewable Energy Laboratory Golden, CO Wind-Diesel Hybrid System Options for Alaska Steve Drouilhet National Renewable Energy Laboratory Golden, CO Wind-Diesel Hybrid Power Systems Basic Concept A wind-diesel hybrid system combines wind turbine(s)

More information

Solar Cybertech: A Competition of Digitally Controlled Vehicles Poweredby Solar Panels

Solar Cybertech: A Competition of Digitally Controlled Vehicles Poweredby Solar Panels 118 ELECTRONICS, VOL. 17, NO. 2, DECEMBER 2013 Solar Cybertech: A Competition of Digitally Controlled Vehicles Poweredby Solar Panels O. García, J. A. Oliver, D. Díaz, D. Meneses, P. Alou, M. Vasić, J.

More information

Fuel economy improvements for urban driving: Hybrid vs. intelligent vehicles

Fuel economy improvements for urban driving: Hybrid vs. intelligent vehicles Transportation Research Part C 15 (2007) 1 16 www.elsevier.com/locate/trc Fuel economy improvements for urban driving: Hybrid vs. intelligent vehicles Chris Manzie *, Harry Watson, Saman Halgamuge Department

More information

Axial Flux Variable Gap Motor: Application in Vehicle Systems

Axial Flux Variable Gap Motor: Application in Vehicle Systems 22-1-188 Axial Flux Variable Gap Motor: Application in Vehicle Systems Sung Chul Oh, Justin Kern, Ted Bohn, Aymeric Rousseau, and Maxime Pasquier Argonne National Laboratory Copyright 22 Society of Automotive

More information

Evaluation of the Automatic Transmission Model in HVE Version 7.1

Evaluation of the Automatic Transmission Model in HVE Version 7.1 HVE-WP-2010-3 Evaluation of the Automatic Transmission Model in HVE Version 7.1 Copyright 2010 Engineering Dynamic Corporation Eric S. Deyerl, P.E., Michael J. Fitch Dial Engineering ABSTRACT The Automatic

More information

The Road to Electrical Vehicle and Hybrid Evolution in Turkey

The Road to Electrical Vehicle and Hybrid Evolution in Turkey The Road to Electrical Vehicle and Hybrid Evolution in Turkey Prof. Dr. R. Nejat TUNCAY OKAN University & MEKATRO R&D Company Istanbul, Turkey November 18, 2015 Why What Happened between 1890 and 1920?

More information

Control Development and Modeling for Flexible DC Grids in Modelica

Control Development and Modeling for Flexible DC Grids in Modelica Control Development and Modeling for Flexible DC Grids in Modelica Andreas Olenmark 1 Jens Sloth 2 Anna Johnsson 3 Carl Wilhelmsson 3 Jörgen Svensson 4 1 One Nordic AB, Sweden, andreas.olenmark@one-nordic.se.

More information

Flux Conference 2012. High Efficiency Motor Design for Electric Vehicles

Flux Conference 2012. High Efficiency Motor Design for Electric Vehicles Flux Conference 2012 High Efficiency Motor Design for Electric Vehicles L. Chen, J. Wang, P. Lombard, P. Lazari and V. Leconte University of Sheffield, Date CEDRAT : 18 October 2012 Presented by: P. Lazari

More information

Platform Engineering Applied to Plug-In Hybrid Electric Vehicles

Platform Engineering Applied to Plug-In Hybrid Electric Vehicles NREL/CP-540-41034. Posted with permission. Presented at the 2007 SAE World Congress April 16-19, 2007, Detroit, Michigan 2007-01-0292 Platform Engineering Applied to Plug-In Hybrid Electric Vehicles Tony

More information

M.S Ramaiah School of Advanced Studies - Bangalore. On completion of this session, the delegate will understand and be able to appriciate:

M.S Ramaiah School of Advanced Studies - Bangalore. On completion of this session, the delegate will understand and be able to appriciate: Transmission Control Lecture delivered by: Prof. Ashok C.Meti MSRSAS-Bangalore 1 Session Objectives On completion of this session, the delegate will understand and be able to appriciate: Rl Role of electronic

More information

Implementation of the Movable Photovoltaic Array to Increase Output Power of the Solar Cells

Implementation of the Movable Photovoltaic Array to Increase Output Power of the Solar Cells Implementation of the Movable Photovoltaic Array to Increase Output Power of the Solar Cells Hassan Moghbelli *, Robert Vartanian ** * Texas A&M University, Dept. of Mathematics **Iranian Solar Energy

More information

Dual Axis Sun Tracking System with PV Panel as the Sensor, Utilizing Electrical Characteristic of the Solar Panel to Determine Insolation

Dual Axis Sun Tracking System with PV Panel as the Sensor, Utilizing Electrical Characteristic of the Solar Panel to Determine Insolation Dual Axis Sun Tracking System with PV Panel as the Sensor, Utilizing Electrical Characteristic of the Solar Panel to Determine Insolation Freddy Wilyanto Suwandi Abstract This paper describes the design

More information

HOMER Software Training Guide for Renewable Energy Base Station Design. Areef Kassam Field Implementation Manager

HOMER Software Training Guide for Renewable Energy Base Station Design. Areef Kassam Field Implementation Manager HOMER Training Guide for Renewable Energy Base Station Design Areef Kassam Field Implementation Manager Solar Table of Contents Introduction Step Step Step Step Solar Step Step Step Step Solar Introduction

More information

Engine Optimization Concepts for CVT-Hybrid Systems to Obtain the Best Performance and Fuel Efficiency. Professor Andrew A. Frank Univ.

Engine Optimization Concepts for CVT-Hybrid Systems to Obtain the Best Performance and Fuel Efficiency. Professor Andrew A. Frank Univ. Engine Optimization Concepts for CVT-Hybrid Systems to Obtain the Best Performance and Fuel Efficiency Professor Andrew A. Frank Univ. of CA-Davis Abstract: The objective of the advanced transmission system

More information

Data Mining in Vehicular Sensor Networks: Technical and Marketing Challenges

Data Mining in Vehicular Sensor Networks: Technical and Marketing Challenges Data Mining in Vehicular Sensor Networks: Technical and Marketing Challenges Hillol Kargupta Agnik & University of Maryland, Baltimore County http://www.cs.umbc.edu/~hillol http://www.agnik.com Roadmap

More information

Adaptive Cruise Control of a Passenger Car Using Hybrid of Sliding Mode Control and Fuzzy Logic Control

Adaptive Cruise Control of a Passenger Car Using Hybrid of Sliding Mode Control and Fuzzy Logic Control Adaptive Cruise Control of a assenger Car Using Hybrid of Sliding Mode Control and Fuzzy Logic Control Somphong Thanok, Manukid arnichkun School of Engineering and Technology, Asian Institute of Technology,

More information

Solar Energy Conversion using MIAC. by Tharowat Mohamed Ali, May 2011

Solar Energy Conversion using MIAC. by Tharowat Mohamed Ali, May 2011 Solar Energy Conversion using MIAC by Tharowat Mohamed Ali, May 2011 Abstract This work introduces an approach to the design of a boost converter for a photovoltaic (PV) system using the MIAC. The converter

More information

Integrating Data, Performing Quality Assurance, and Validating the Vehicle Model for the 2004 Prius Using PSAT

Integrating Data, Performing Quality Assurance, and Validating the Vehicle Model for the 2004 Prius Using PSAT 26 1-667 Integrating Data, Performing Quality Assurance, and Validating the Vehicle Model for the 24 Prius Using PSAT Copyright 26 SAE International A. Rousseau, J. Kwon, P. Sharer, S. Pagerit, M. Duoba

More information

DESIGN AND DEVELOPMENT OF UTILITY INTERFACE ADAPTIVE SOLAR POWER CONVERTER FOR WATER PUMPING SYSTEM IN INDIAN VILLAGES

DESIGN AND DEVELOPMENT OF UTILITY INTERFACE ADAPTIVE SOLAR POWER CONVERTER FOR WATER PUMPING SYSTEM IN INDIAN VILLAGES DESIGN AND DEVELOPMENT OF UTILITY INTERFACE ADAPTIVE SOLAR POWER CONVERTER FOR WATER PUMPING SYSTEM IN INDIAN VILLAGES 1 S. N. Singh, 2 Snehlata Mishra & 3 Vandana Neha Tigga Department of Electronics

More information

LINEAR MOTOR CONTROL IN ACTIVE SUSPENSION SYSTEMS

LINEAR MOTOR CONTROL IN ACTIVE SUSPENSION SYSTEMS LINEAR MOTOR CONTROL IN ACTIVE SUSPENSION SYSTEMS HONCŮ JAROSLAV, HYNIOVÁ KATEŘINA, STŘÍBRSKÝ ANTONÍN Department of Control Engineering, Faculty of Electrical Engineering, Czech Technical University Karlovo

More information

Impact of Reflectors on Solar Energy Systems

Impact of Reflectors on Solar Energy Systems Impact of Reflectors on Solar Energy Systems J. Rizk, and M. H. Nagrial Abstract The paper aims to show that implementing different types of reflectors in solar energy systems, will dramatically improve

More information

Hybrid shunter locomotive

Hybrid shunter locomotive Hybrid shunter locomotive 1 Hervé GIRARD, Presenting Author, 2 Jolt Oostra, Coauthor, 3 Joerg Neubauer, Coauthor Alstom Transport, Paris, France 1 ; Alstom Transport, Ridderkerk, Netherlands 2 ; Alstom

More information

An Isolated Multiport DC-DC Converter for Different Renewable Energy Sources

An Isolated Multiport DC-DC Converter for Different Renewable Energy Sources An Isolated Multiport DC-DC Converter for Different Renewable Energy Sources K.Pradeepkumar 1, J.Sudesh Johny 2 PG Student [Power Electronics & Drives], Dept. of EEE, Sri Ramakrishna Engineering College,

More information

TRAMS TROLLEY-BUSES SUBWAY

TRAMS TROLLEY-BUSES SUBWAY 9 FT-100-600 Traction Inverter for Asynchronous Drives 11 FT-105-600 Traction Inverter for Asynchronous Drives 13 FT-170-600 Traction Inverter for Asynchronous Drives 15 FT-300-600 Traction Inverter for

More information

Cost-Benefit Analysis of Plug-In Hybrid- Electric Vehicle Technology

Cost-Benefit Analysis of Plug-In Hybrid- Electric Vehicle Technology NREL/PR-540-40847 Cost-Benefit Analysis of Plug-In Hybrid- Electric Vehicle Technology 22 nd International Electric Vehicle Symposium Yokohama, Japan October 25-28, 2006 Ahmad Pesaran for Andrew Simpson

More information

Hybrid Power System with A Two-Input Power Converter

Hybrid Power System with A Two-Input Power Converter Hybrid Power System with A Two-Input Power Converter Y. L. Juan and H. Y. Yang Department of Electrical Engineering National Changhua University of Education Jin-De Campus, Address: No.1, Jin-De Road,

More information

Photovoltaic Solar Energy Unit EESFB

Photovoltaic Solar Energy Unit EESFB Technical Teaching Equipment Photovoltaic Solar Energy Unit EESFB Products Products range Units 5.-Energy Electronic console PROCESS DIAGRAM AND UNIT ELEMENTS ALLOCATION Worlddidac Member ISO 9000: Quality

More information

Fault codes DM1. Industrial engines DC09, DC13, DC16. Marine engines DI09, DI13, DI16 INSTALLATION MANUAL. 03:10 Issue 5.0 en-gb 1

Fault codes DM1. Industrial engines DC09, DC13, DC16. Marine engines DI09, DI13, DI16 INSTALLATION MANUAL. 03:10 Issue 5.0 en-gb 1 Fault codes DM1 Industrial engines DC09, DC13, DC16 Marine engines DI09, DI13, DI16 03:10 Issue 5.0 en-gb 1 DM1...3 Abbreviations...3 Fault type identifier...3...4 03:10 Issue 5.0 en-gb 2 DM1 DM1 Fault

More information

Alternative Drivetrains Volkswagen Group s Solutions for Sustainable Mobility

Alternative Drivetrains Volkswagen Group s Solutions for Sustainable Mobility Alternative Drivetrains Volkswagen Group s Solutions for Sustainable Mobility Prof. Dr. Wolfgang Steiger Group External Relations Future Technologies 2013-10-02 E-mobil BW Technologietag Stuttgart, Germany

More information

Energy Storage System for Dc Micro Grid Using PIC Microcontroller

Energy Storage System for Dc Micro Grid Using PIC Microcontroller Energy Storage System for Dc Micro Grid Using PIC Microcontroller Sanas Renuka V 1, Patil Anupama S 2 P.G. Student, Department of Electrical Engg, Dnyanganga College of Engineering & Research, Pune, India

More information

Pure Efficiency. C.C.I.A.A.: N REA. 0195268 Cod. Fiscale e P. IVA: 00483230173 Capitale Sociale versato 100.000,00

Pure Efficiency. C.C.I.A.A.: N REA. 0195268 Cod. Fiscale e P. IVA: 00483230173 Capitale Sociale versato 100.000,00 Pure Efficiency. The need to significantly reduce the production costs to remain competitive on the global market and the requirement to control and lessen the environmental impact of all activities are

More information

Electric motor emulator versus rotating test rig

Electric motor emulator versus rotating test rig DEVELOPMENT E l e c t r i c m o t o r s Electric motor emulator versus rotating test rig A controversial issue among experts is whether real-time model-based electric motor emulation can replace a conventional

More information

An Approach for Designing Thermal Management Systems for EV and HEV Battery Packs

An Approach for Designing Thermal Management Systems for EV and HEV Battery Packs An Approach for Designing Thermal Management Systems for EV and HEV Battery Packs 4th Vehicle Thermal Management Systems Conference London, UK May 24-27, 1999 Ahmad A. Pesaran, Ph.D. Steven D. Burch Matthew

More information

EPoSS Strategy Paper Smart Systems for the Full Electric Vehicle

EPoSS Strategy Paper Smart Systems for the Full Electric Vehicle Joint EC/EPoSS Expert Workshop Smart Systems for the Full Electric Vehicle Brussels 25-26 June 2008 EPoSS Strategy Paper Smart Systems for the Full Electric Vehicle August 2008 1. Introduction Growing

More information

Coordination Control of a Hybrid AC/DC Microgrid With Various Renewable Energy Sources

Coordination Control of a Hybrid AC/DC Microgrid With Various Renewable Energy Sources Coordination Control of a Hybrid AC/DC Microgrid With Various Renewable Energy Sources 1 Hema Surya Teja Beram, 2 Nandigam Rama Narayana 1,2 Dept. of EEE, Sir C R Reddy College of Engineering, Eluru, AP,

More information

Design, Analysis, and Implementation of Solar Power Optimizer for DC Distribution System

Design, Analysis, and Implementation of Solar Power Optimizer for DC Distribution System Design, Analysis, and Implementation of Solar Power Optimizer for DC Distribution System Thatipamula Venkatesh M.Tech, Power System Control and Automation, Department of Electrical & Electronics Engineering,

More information

Analysis of Ultracapacitor-VRLA Energy Storage Systems for Mild Hybrids

Analysis of Ultracapacitor-VRLA Energy Storage Systems for Mild Hybrids Analysis of Ultracapacitor-VRLA Energy Storage Systems for Mild Hybrids Tony Markel, Ahmad Pesaran, and Sam Sprik ahmad_pesaran@nrel.gov 5 th Advanced Automotive Battery Conference Honolulu, Hawaii June

More information

A Wireless Power Transfer system for electric vehicle in Charge While Driving

A Wireless Power Transfer system for electric vehicle in Charge While Driving A Wireless Power Transfer system for electric vehicle in Charge While Driving Author: Vincenzo Cirimele ID 21712 First year PhD student Tutor: Professor Fabio Freschi Collaborators in the research: Prof.

More information

INTEGRATED OPEN DEVELOPMENT PLATTFORM FÜR TEIL- UND VOLLAUTOMATISIERTE FAHRZEUGANTRIEBE

INTEGRATED OPEN DEVELOPMENT PLATTFORM FÜR TEIL- UND VOLLAUTOMATISIERTE FAHRZEUGANTRIEBE INTEGRATED OPEN DEVELOPMENT PLATTFORM FÜR TEIL- UND VOLLAUTOMATISIERTE FAHRZEUGANTRIEBE PETER PRENNINGER A3PS MV - Peter Prenninger 2014-12-11 1 SUSTAINABILITY REQUIRES AN EFFICIENT MOBILITY SYSTEM Infrastructure

More information

Study of 100kW solar PV plant installed at main building rooftop

Study of 100kW solar PV plant installed at main building rooftop Study of 100kW solar PV plant installed at main building rooftop Experiment manual Introduction: The energy plays a pivotal role in our daily activities. The degree of development of a country is measured

More information

Argonne s vehicle systems research Future

Argonne s vehicle systems research Future Argonne s vehicle systems research Future Driving the Accelerating the adoption of New Technologies At Argonne National Laboratory s Center for Transportation Research, our goal is to accelerate the development

More information

Shell Eco-Marathon. Engineering Analysis Document

Shell Eco-Marathon. Engineering Analysis Document Shell Eco-Marathon By Abdul Alshodokhi, John Gamble, Nikolaus Glassy, and Travis Moore Team 14b Engineering Analysis Document Submitted towards partial fulfillment of the requirements for Mechanical Engineering

More information

INTERFACES FOR RENEWABLE ENERGY SOURCES WITH ELECTRIC POWER SYSTEMS

INTERFACES FOR RENEWABLE ENERGY SOURCES WITH ELECTRIC POWER SYSTEMS INTERFACES FOR RENEWABLE ENERGY SOURCES WITH ELECTRIC POWER SYSTEMS Paulo Ferreira, Manuel Trindade, Júlio S. Martins and João L. Afonso University of Minho, Braga, Portugal paulo.alves.ferreira@sapo.pt,

More information

DYNAMICS AND EFFICIENCY: THE ALL NEW BMW i8 PLUG-IN-HYBRID.

DYNAMICS AND EFFICIENCY: THE ALL NEW BMW i8 PLUG-IN-HYBRID. Wien, 20.November 2014 DYNAMICS AND EFFICIENCY: THE ALL NEW BMW i8 PLUG-IN-HYBRID. CHRISTIAN LANDERL. IN A CHANGING WORLD, E-MOBILITY IS AN INTERESTING APPROACH. Environment Emissions and climate change

More information

Making Accurate Voltage Noise and Current Noise Measurements on Operational Amplifiers Down to 0.1Hz

Making Accurate Voltage Noise and Current Noise Measurements on Operational Amplifiers Down to 0.1Hz Author: Don LaFontaine Making Accurate Voltage Noise and Current Noise Measurements on Operational Amplifiers Down to 0.1Hz Abstract Making accurate voltage and current noise measurements on op amps in

More information

FEV Parallel Mode Strategy

FEV Parallel Mode Strategy FEV Parallel Mode Strategy Peter Janssen MSc. Dipl.-Ing Glenn Haverkort FEV Motorentechnik As the automotive industry has to react to the global concern about climate change related to CO2 emissions and

More information

Automation System TROVIS 6400 TROVIS 6493 Compact Controller

Automation System TROVIS 6400 TROVIS 6493 Compact Controller Automation System TROVIS 6400 TROVIS 6493 Compact Controller For panel mounting (front frame 48 x 96 mm/1.89 x 3.78 inch) Application Digital controller to automate industrial and process plants for general

More information

Solid Oxide Fuel Cell Gas Turbine Hybrid Power Plant. M. Henke, C. Willich, M. Steilen, J. Kallo, K. A. Friedrich

Solid Oxide Fuel Cell Gas Turbine Hybrid Power Plant. M. Henke, C. Willich, M. Steilen, J. Kallo, K. A. Friedrich www.dlr.de Chart 1 > SOFC XIII > Moritz Henke > October 7, 2013 Solid Oxide Fuel Cell Gas Turbine Hybrid Power Plant M. Henke, C. Willich, M. Steilen, J. Kallo, K. A. Friedrich www.dlr.de Chart 2 > SOFC

More information

Hybrid Micro-Power Energy Station; Design and Optimization by Using HOMER Modeling Software

Hybrid Micro-Power Energy Station; Design and Optimization by Using HOMER Modeling Software Hybrid Micro-Power Energy Station; Design and Optimization by Using HOMER Modeling Software Iyad. M. Muslih 1, Yehya Abdellatif 2 1 Department of Mechanical and Industrial Engineering, Applied Science

More information

Electric Vehicle Performance and Consumption Evaluation

Electric Vehicle Performance and Consumption Evaluation World Electric Vehicle Journal Vol. 6 - ISSN 232-6653 - 213 WEVA Page Page 3 EVS27 Barcelona, Spain, November 17-2, 213 Electric Vehicle Performance and Consumption Evaluation Mohamed El Baghdadi 1, Laurent

More information

Energy Recovery System for Excavators Meng (Rachel) Wang, Chad Larish Eaton Corporation

Energy Recovery System for Excavators Meng (Rachel) Wang, Chad Larish Eaton Corporation Energy Recovery System for Excavators Meng (Rachel) Wang, Chad Larish Eaton Corporation Abstract Increasing fuel costs have become a significant portion of the operating expenses for owners and fleet managers

More information

Clean and energy-efficient vehicles Advanced research and testing Battery systems

Clean and energy-efficient vehicles Advanced research and testing Battery systems Clean and energy-efficient vehicles Advanced research and testing Battery systems Flanders DRIVE Index: Flanders DRIVE 1 Optimising power / energy ratio of energy storage systems 4 Battery ageing research

More information